TimeSeries [Aptech Systems, Inc.]

Time-Series Cross-Sectional Regression Models, Autoreggression Models,ARIMA-estimation.Time-Series Cross Sectional Regression Models: TSCSThis module provides procedures to compute estimates for "pooled time-series, cross-sectional units (e.g., people, firms, countries). Forexample, the analyst may have data for a cross-section of individualseach measured over 10 time periods. While these models were devised tostudy a cross-section of units over multiple time periods, they alsocorrespond to models in which there are data for groups such as schoolsor firms with measurements on multiple observations within the group(e.g., students, teachers, employees).The specific model that can be estimated with this program is aregression model with variable intercepts. That is, a model withindividual-specific effects. The regression parameters for the exogenousvariables are assumed to be constant cross-sectional units. The interceptvaries across individuals.This program provides three estimators:* Fixed-effects OLS estimator (analysis of covariance estimator)* Constrained OLS estimator* Random effects estmator using GLSA Hausman test is computed to show whether the error components (randomeffects) model is the correct specification, In addition to providing theanalysis of covariance and GLS estimates, two multiple partial-squaredcorrelations are computed. The first partial correlation (squaredcorrelation) shows the percentage of variation in the dependent variablethat can be explained by the set of independent variables while holdingconstant and group variables. The second estimate shows the extent towhich variation in the dependent variable can be accounted for by thegroup variable after the other independent variables have beenstatistically held constant.A key feature of this program is that it allows for a variable number oftime-series observations per cross-sectional unit. For instance, theremight be 5 time-series observations for the first individual, 10 for thesecond, and so on. This is useful where there are missing values.Autoregression Models: AUTOREGAUTOREG will compute estimates of the parameters and standard errors fora regression model with autoregressive errors. Thus, it can be used formodels for which the Cochrane-Orcutt or similar procedure can be used. Itis also similar to the SAS AUTOREG procedure except that this routinewill compute the maximum likelihood estimates based upon the exactlikelihood function.

Source Avail: No
Product Special Handling: None.
Operating Systems: Solaris Sparc 1.0,2.0,2.1,2.2,2.3,2.4 Solaris x86 2.0,2.1,2.2,2.3,2.4

Aptech Systems, Inc.
23804 SE Kent Kangley Rd
Maple Valley, WA 98038
USA
Phone: (206) 432-7855
Fax: (206) 432-7832

Econometric Modeling/Analysis

TimeSeries

Aptech Systems, Inc.